Battle Swarm: An Evolutionary Approach to

Complex Swarm Intelligence

Russel Ahmed ApuMarina Gavrilova

Brief Outline

• Battle Swarms• Tactics and battle efficiency• Swarm Intelligence: Missile Genotype Encoding• Evolutionary strategies for battle swarms• Experimental results and analysis

Objective:To utilize swarm based tactics & evolutionary

swarm strategies to increase tactical efficiency for offensive and defensive agents

Battle Swarms Agents

• MISSILES

• Autonomous• Limited sensory

capabilities• Limited intelligence• Single objective: Hit ship• Complex dynamic system• Behavior of one missile

effect other missiles in the swarm

• Evolutionary Strategy

• DEFENSE TURRETS

• Point Defense system• Only Visual/radar

capabilities• Limited coverage• Single Objective: Destroy

missiles • Simple rule, complex

outcome: Select and fire• Behavior and efficiency

cruicial to survival• Fixed Strategy

Defense Mechanism

Missile

Missile

Missile

Point Defense

Reaction Radius

Reaction

Actions of a Missile

Constant Thrust

Right

Up

Heading

ROLL LEFT

ROLL RIGHT

PITCH DOWN

Action Encoding Set: {LRUDNMFAXYZ}* X=Rand Y=Converge*

L= Roll Left U=Pitch Up N=NOP F=Follow* Z=Diverge*

R=Roll Right D=Pitch Down M=Memory A=Avoid*

* Discussed in the next few slides

PITCH UP

Basic Sensory Encoding and Actions

COG

Follow Target

Projection Plane

(1)

Roll to match proj(v)=proj(u)

(2)

Pitch upProj(v)

Proj(u)

Basic Sensory Encoding and Actions

COG

Avoid Target

Projection Plane

(1)

Roll to match proj(v).proj(u)=0

(2)

Pitch up

Proj(v)

Proj(u)

Target Relative Coordinate(Range, Heading, Bearing)

x y zf ,f ,f Forward Vector of missile m Up vector of missile m Location of the missile m

Location of the Target

m

m

m

F

upT

= ===

=

rr

( )

( )

( )

( )

2x x y x z

2xx y y z

2xx z y z

f1- -ff -fff-ff 1- -ff=

f-ff -ff 1-Heading, mm ph F

é ùê úê úê úê úê úê úë û= ·

M

Mr

Range, pM TR -=

( ) ( )( )( )Bearing, mm mm mb FT p T pu u= × ·- -· ´M Mr r

Target relative: Heading

Target Relative: Bearing

COG

Projection Plane

u

PRproj

b Rproj

F

Swarm Relative Encoding• Regulates the probability of Flocking Tendency• ‘Y’ Flock and increase tendency (probability of

Boids flocking)• ‘Z’ Diverge from flock and decrease tendency• If an agents decides to flock (prob= ), the direction is

determined using modified BOIDS

Boids flocking: From left to right rules of cohesion, separation and alignment [2].

Decision Making• Event related decision are made by the

swarm implicitly

• Avoiding Incoming fire: Ionization trail gives negative pheromone to allow flocking out of a region

• Finding Weakness in Defense: Combined usage of flocking tendency, gas and ionization pheromone trail

Basic Encoding of Missile genotype • String of Possible Action (I.e [LYUXLY])• Action string is circular (iterative)• Missile DNA=Gene_String[]• Continuous execution of the string • Each action executed for an infinite time• Regulates Swarm Behavior/Tendency

Encoding Basic Maneuvers

• Maintain Current Heading = [N]• Homing the Target = [F]• Ring Motion = [U] • Cork Screw = [LU], [LUMMM]• Evasive Approach = [XF], [XMMMF]• Basic Evasive Action = [A], [AMMMX]• Fall Back = [XU], [XMMMU], [AU]• Scramble = [X]

Basic Maneuvers

[N]

[A]

[U]

[F] [XF]

[LU]

Different Complex Maneuvering Tactics

• Retaliation – frontal attack• Evasive – avoid fire at all costs• Convergent approach – approach target from a

particular direction• Divergent approach – surround and approach from

different directions• Trail wind flocking –one missile leads others • Distract and draw fire

Different Complex Maneuvering Tactical strategies

(a) Diversion (b) Trail Wind Flocking (c) Retaliation (d) Divergence

Mutating and Evolving the Missile Genotype

• Fitness: Define a fitness function for the desired action

• Crossover: Augment/concatenate Genes

{[LUMU] [AMD]} {[LUAMDMU] [LUMD] [AMDUMU] [LMDMU]…}

• Randomization: Replace arbitrary symbols with “X”… run the simulation and convert meta genes to real genes

[FFLLU] [FXLXU] {[FULLU], [FFLFU], [FNLNU], [FMLNU]} Best{[FULLU], [FNLNU]}

Induced Evolution• We can introduce certain desired behavior

in addition to natural evolution

• Step 1: Train Missiles separately to obtain certain desired behavior without any other consideration. Obtain Viral strain W=[…]

• Step 2: Infect All current Genotype with viral Strain W (crossover)

The Game: Co-evolution1. Implement basic missile [F] and basic Turret

{Select X, Fire@trajectory}2. Adjust physical property to match

– Fitness=50% (50% missiles hit the target)

3. Evolve Missiles and turrets against previous strain

4. Repeat step 3 for several Games cycles5. If fitness falls or rises dramatically increase

physical strength of opposing swarm (Missile: Acceleration, velocity, turning. Turrets: Speed of fire, number of turrets, firing frequency)

The Fitness Function: Hetero-Sexual Mating

• Use a two dimensional Fitness Function• Every missile has a masculine and a feminine fitness• Masculine: Ability to Attack• Feminine: Ability to Survive

,i iiW W= J,i iiW W= J

# of missile hitting the target# of missiles launched

# of gunshots successfully evaded# of missiles destroyed+1

i

i

W =

=J

Results

- Strategies evolved, Runtime and other aspects

Fitness Function

05

101520253035404550

0 20 40 60 80 100Masculine

Fem

inin

e

Randomized No Randomization

Evasive

Dispersion

Distraction Swarm: Trail Wind

Assult

Complex Tactics: Convergent Approach

• Strength in numbers• Less exposure to incoming

fire• Increase of spatial threat• Decrease of temporal threat

• High Efficiency• Low evasion• Highly Masculine

Complex Tactics: Divergent Approach• Cause more distraction and

confuse the defense system• Less likelihood for a missile

to draw fire • Decrease of spatial threat• Increase of temporal threat

• Lower Efficiency• Highly Evasive• Highly Feminine

Convergent VS Divergent Approach

• CONVERGENT• Less defense turrets• Draw less fire• Easy to shoot down

• DIVERGENT• More defense turrets• Draw more fire• Distracting and hard to

shoot down

Complex Tactics: Trail Wind Flocking

• Better than “Convergent Approach”• Least exposure to incoming fire• Lot of opportunity for diversion/distraction• Decrease of spatial threat• Decrease of average temporal threat

More Results

(a) Funnel Shaped Assault

(b) Parachute Phase 1: Forming a moth ball

(c) Parachute Phase 2: Dispersing

(d) Parachute Phase3: Forming a Head

(e) Parachute Phase 4: Trail Wind Attack

(f) Divergent Attack

More ResultsFigure 11: Formation of Distraction, Organic and Deception pattern

(h) Distraction 2: Assault in progress

(g) Distraction 1: Early missiles draw fire

(i) Organic motion pattern

(j) Deception 1: Lead Assault

(k) Deception 2: Overshooting the target

(l) Deception 3: Come about and attack

More Results

See Animation Demos

Rendering and Physical Engine• Regular physics engine will not suffice

– Approximation aggravates trajectory computation

• Construct everything from scratch– Advanced look-ahead estimation based physics

engine – Robust Rendering engine:

• Anisotropic Texture filtering • Multiple LOD based geometry rendering• Particle engine • Highly optimized exclusive API for performance• Flexibility

The Simulation Engine• Robust design: Separation of Rendering

modules from the simulation• Implements Command Console• Runtime performance is highly efficient• For 50 missiles:

– Full quality rendering@ 50FPS !!!– Simulation runs upto 50 times faster

(FPS=2200+) is rendering is turned off (for evolutionary algorithm)

– Excellent Rendering quality (anisotropic texture mapping, particle engine)

Runtime PerformancePerformance of Different Runtime Modes

38.1698.72

391.74

48.77110.33

715.73

0

100

200

300

400

500

600

700

800

Mode

Fram

e/Se

cond

Summary• Using Swarm Intelligence to evolve battle tactics for

– Missiles– Point Defense Turrets

• Evolutionary strategies:– Gene_String[] evolution– The novel “Induced Evolution” strategy– Co-evolutionary strategy

• Implementation: – Rendering and physical Engine– Genotype encoding– Basic maneuvers– Complex maneuvers– Integration

Thank you